Learning to Coordinate with Anyone

Understand

In open multi-agent environments, the agents may encounter unexpected teammates.

• Classical multi-agent learning approaches train agents that can only coordinate with seen teammates.
• Recent studies attempted to generate diverse teammates to enhance the generalizable coordination ability, but were restricted by pre-defined teammates.
• In this work, our aim is to train agents with strong coordination ability by generating teammates that fully cover the teammate policy space, so that agents can coordinate with any teammates.